We often require the analysis of data in which certain features are grouped in different regions, each with different sizes, values, shapes, and so on. The scipy.ndimage.measurements submodule has the right tools for this task, and the best way to illustrate the capabilities of the module is by means of exhaustive examples. For example, for binary images of zeros and ones, it is possible to label each blob (areas of contiguous pixels with value one) and obtain the number of these with the label command. If we desire to obtain the center of mass of the blobs, we may do so with the center_of_mass command. We may see these operations in action once again in the application to obtain the structural model of oxides in Chapter 7, SciPy for Computational Geometry.

For nonbinary data, the scipy.ndimage.measurements submodule provides the usual basic statistical measurements (value and location of extreme values, mean, standard deviation, sum, variance, histogram, and so on...